Senior Data Engineer (Python, Azure Fabric, PySpark) - Model N

Job Title: Senior Data Engineer (Python, Azure Fabric, PySpark)
Job Location: Hyderabad India
Job Listing URL: https://jobs.lever.co/modeln/cb62375b-e566-4a9d-aa29-73ad5a5d142d
Job Description: Model N is seeking an experienced and innovative Data Architect/Engineer to join our newly formed Client Analytics team. This is a unique opportunity to join at the ground level and play a key role in building an analytics platform that delivers high-value insights and production-ready models across the organization.
The ideal candidate will have extensive experience integrating disparate data sources into a scalable, robust data architecture that empowers analytics and machine learning initiatives. A strong customer focus and the ability to independently plan, prioritize, and execute multiple projects in parallel are essential.
If you thrive in a fast-paced, evolving environment and want to help shape the future of analytics at Model N, we want to hear from you.
Job Responsibilities
Lead the design and implementation of scalable data infrastructure and pipelines in collaboration with IT, enabling secure and high-performance access to Azure Fabric lakehouses to support reporting, advanced analytics, and machine learning use cases.
Collaborate with analysts and stakeholders to translate business questions and model requirements into structured data workflows and repeatable, automated processes.
Implement and manage data ingestion and transformation workflows across diverse sources using tools such as Python, PySpark, SQL, Azure Data Factory, and Microsoft Fabric.
Enable batch model scoring pipelines, manage model artifacts and outputs, and ensure timely delivery of results to reporting environments (e.g., Power BI datasets).
Ensure data quality, lineage, and governance, implementing validation rules and monitoring to support trusted analytics and reproducibility.
Act as a technical advisor and partner to the analytics team, helping define data requirements and optimize model performance through better data design and availability.
Continuously evaluate emerging data technologies and practices, recommending improvements to infrastructure, tooling, and processes that enhance analytical agility and scale.
Job Skills
5–8 years of experience in data engineering, data architecture, or analytics infrastructure roles.
Proven track record of designing and deploying scalable data pipelines and structured data assets in modern cloud environments.
Hands-on experience managing data pipelines for machine learning, including support for model deployment and scoring workflows.
Experience working cross-functionally with business, analytics, and product teams to align data capabilities with strategic needs.
Familiarity with customer analytics concepts, including segmentation, churn, and lifecycle metrics.
Technical Skills
Strong hands-on experience with Azure Fabric, Lakehouses, and Microsoft Fabric pipelines.
Proficient in Python for building and automating data workflows, including cleansing and writing to cloud storage.
Expertise in SQL for data extraction, transformation, and performance tuning.
Experience with semantic modeling (e.g., using DAX, Power BI datasets) to support self-service analytics.
Understanding of data warehouse design principles, including star/snowflake schemas and slowly changing dimensions.
Exposure to CRM systems (e.g., Salesforce) and version control tools (e.g., Git).
Familiarity with MLOps workflows, including model versioning, batch scoring, and result storage.
Bachelor’s degree in a quantitative or technical field (e.g., Computer Science, Data Engineering, Information Systems, Data Science, or related disciplines).
Master’s degree preferred in Data Engineering, Computer Science, or a related field.